POS0214 IN-DEPTH ANALYSIS OF DISEASE MANIFESTATIONS IN ANCA-ASSOCIATED VASCULITIDES IDENTIFIES DISTINCT CLINICAL PHENOTYPES, EMPHASIZING THE IMPACT OF SEX AND AGE AT DIAGNOSIS
Authors: H. Lindberg, S. Rantapää Dahlqvist, O. Norling, E. Hellbacher, E. Berglin, B. Stegmayr, B. Baslund, Ø. Palm, H. Haukeland, I. Gunnarsson, A. Bruchfeld, M. Segelmark, S. Olsson, A. J. Mohammad, A. Svärd, R. Pullerits, H. Herlitz, A. Soderbergh, P. Eriksson, A. Knight, J. Dahlqvist
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA), two different ANCA-associated vasculitides (AAV), are clinically heterogeneous. Little is known about potential differences in clinical presentation of disease between females and males and between patients diagnosed at a young versus at an older age. Likewise, associations between different clinical manifestations have not been thoroughly investigated. <h3>Objectives</h3> To improve care and prediction of outcome in patients with AAV, the aims of this study were to identify and thoroughly characterize subgroups of AAV patients, stratified for sex, age at diagnosis and clinical manifestations. <h3>Methods</h3> In a systematic multicenter study, adult patients diagnosed with GPA or MPA were included between 2008-2018. Clinical data including sex, age at diagnosis, ANCA-specificity, relapse and cumulative disease involvement of ear-nose-throat (ENT), lungs, eyes, kidneys, muscles/joints, skin, central nervous system (CNS), peripheral nervous system (PNS), gastrointestinal tract (GI) and heart were collected from medical records. Organ involvements were analyzed for associations with sex, age at diagnosis and relapse, in GPA and MPA, separately, using logistic regression. Agglomerative hierarchical cluster analysis was performed using the Ward method, based on the n number of axes explaining ≥90% of total variability in multiple correspondence analysis of the collected clinical data in GPA and MPA. The optimal number of clusters was estimated by determining the gain in within-cluster inertia achieved at each clustering step<sup>[1]</sup>. <h3>Results</h3> In total, 1156 patients (578 females, 578 males) were included in the study; 922 were classified as GPA, 234 as MPA. In GPA, pulmonary and renal involvement, as well as PR3-ANCA, were significantly associated with male sex, whereas MPO-ANCA was associated with female sex. In MPA, the only difference between the sexes was an older age at diagnosis in males than females. In GPA, the age at diagnosis showed a bimodal pattern with two peaks of incidence with mean (range) at 22.4 (9-31) and 57.1 (32-91) years of age, respectively. Comparing GPA patients younger than 32 years old at diagnosis with those older than 32 identified a significantly higher prevalence of females, ENT- and GI involvement and relapse rate in the younger group and PNS involvement in the older group. In all GPA patients, relapse was associated with pulmonary involvement, whereas in MPA relapse was associated with musculoskeletal involvement. Hierarchical cluster analysis of GPA and MPA identified five and seven distinct clusters, respectively. For both diseases, three of the clusters were defined by heart-, CNS- and GI involvement, respectively. In GPA, the largest cluster was defined by PR3-ANCA and ENT involvement and the fifth cluster by MPO-ANCA, female dominance and a low rate of ENT involvement. The additional four clusters in MPA were defined by i) eye involvement, ii) absence of renal involvement, iii) PR3-ANCA and iv) MPO-ANCA with renal involvement (largest), respectively. In addition, in several of the clusters in both GPA and MPA, there was a significant enrichment or depletion of additional clinical manifestations, in comparison with the largest cluster. <h3>Conclusion</h3> The results of this study indicate distinct disease courses of GPA in females and males, and strongly suggest that sex and age at diagnosis should be considered in the clinical assessment of disease outcome in GPA patients. The identification of associations between different clinical manifestations in the cluster analysis may facilitate the prediction of organ involvements in patients with AAV, and, subsequently, clinical decision-making. <h3>Reference</h3> [1]Mahr, A. <i>et al.</i> Revisiting the classification of clinical phenotypes of anti-neutrophil cytoplasmic antibody-associated vasculitis: a cluster analysis. <i>Ann Rheum Dis</i><b>72</b>, 1003-10 (2013). <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.